This $2,380,018 Project Grant award from the National Institute on Aging's Aging Research Federal Grant Program (CFDA 93.866) will fund a comprehensive study on the influence of type 2 diabetes and prediabetes on cognitive decline and Alzheimer's disease risk. The award to the Regents of the University of Michigan will quantify the effects of cumulative hyperglycemia and diabetes management on cognitive trajectories and neuroimaging markers of cerebrovascular disease, with the goal of guiding...
The National Institute on Aging (NIA) awarded a $661,016 Project Grant (CFDA 93.866 - Aging Research) to the University of Southern California (USC) to develop a "Federated Deep Learning to Accelerate Alzheimer's Disease Research" platform. This project aims to leverage innovative artificial intelligence (AI) techniques and distributed computing to analyze Alzheimer's disease (AD) biobanks from the U.S., India, Japan, and Europe, totaling over 100,000 MRI and PET scans. The key...
The University of Michigan was awarded a $1.1 million Project Grant from the National Science Foundation Division of Mathematical Sciences under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will fund research from September 2021 through August 2025 to develop new statistical learning methods for brain-computer interfaces. As part of the Computer and Information Science and Engineering program's goals of supporting investigator-initiated research and...
This National Science Foundation (NSF) Project Grant award to Wake Forest University, under the Computer and Information Science and Engineering (CFDA 47.070) program, aims to develop a "Neuron Twin" computational system that simulates the human brain to improve understanding and predictions related to Alzheimer's disease. The $501,329 five-year project will leverage deep learning and multiscale modeling to jointly analyze multimodal data, including genetic, neuroimaging, and...
This $1,933,556 Project Grant awarded by the National Institute on Aging (NIA) under its Aging Research program (CFDA 93.866) will support research to assess the impact of hospital-based health information technology (hospital-HIT) on healthcare quality and equity for patients with Alzheimer's disease and related dementias (ADRD). The primary awardee, the University of Maryland, College Park, will conduct a ten-year longitudinal study to evaluate how hospital-HIT systems that promote care...
This Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) provides $778,499 to the University of Texas Health Science Center at Houston to develop novel machine learning models to identify and stratify heterogeneous subpopulations of Alzheimer's disease (AD) patients based on risk and progression patterns. The goal is to transform these subtypes into potentially targetable groups to enable focused clinical trials, support future therapeutic development, and...
This $320,502 Project Grant award from the National Science Foundation (NSF) Division of Information and Intelligent Systems is for a collaborative research project titled "Knowledge Discovery from Highly Heterogeneous, Sparse and Private Data in Biomedical Informatics." The research aims to mine healthcare data to identify patients likely to develop chronic conditions like type 2 diabetes and heart failure, and to develop models for opportunistic screening, particularly for...
This federal Project Grant award, provided by the National Institute on Aging under CFDA 93.866 Aging Research, aims to develop explainable and ethical artificial intelligence (AI) models to assist in the diagnosis and prognosis of Alzheimer's disease (AD). The $738,014 award to Emory University, with a period of performance from August 1, 2024 to April 30, 2029, will leverage the institution's expertise in explainable AI, cerebrospinal fluid proteomics, and understanding the role of factors...
This $170,000 federal Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop robust and human-aligned deep learning techniques for analyzing medical sensor time-series data. The primary goals are to: 1) identify input confounders that lead to spurious correlations in time-series data, 2) design knowledge-editing strategies to correct these spurious correlations, and 3) investigate the techniques...
This $287,118 Project Grant was awarded on September 1, 2023 by the National Institute on Aging (NIA) under the Aging Research (CFDA 93.866) grant program. The grant will fund the development of techniques to use deep transfer learning and multimodal data, including brain MRIs, genetic information, and cognitive tests, to enable the early detection and forecasting of Alzheimer's disease progression. The University of Massachusetts (UMass), as the prime awardee, will create an end-to-end...